Metagenomics: MAG (Metagenome-Assembled Genome)

Basic Protocol 1: MAG Data Processing Workflow

This README outlines the steps to set up and run a basic protocol for MAG data processing using sra-tools, fastp, and FastQC. These tools are critical for fetching, cleaning, and validating the quality of sequencing data. Each tool/package plays a specific role in ensuring the integrity and usability of the sequence data for downstream analysis.

Requirements

• macOS
• Conda (Miniconda or Anaconda)
• Command-line (Terminal)

Environment Setup

Step 1: Create and Activate Conda Environment

Conda is a widely-used environment management system, essential for managing dependencies, isolating project environments, and ensuring reproducibility.

conda create -n Basic_protocol_1
conda activate Basic_protocol_1

Step 2: Configure Conda Channels

Adding the right Conda channels is important because some bioinformatics tools are hosted on specific repositories (like bioconda and conda-forge). These repositories are curated to ensure compatibility and updates for bioinformatics tools.

conda config --add channels bioconda
conda config --add channels conda-forge

Step 3: Install Required Tools

sra-tools

• Purpose: sra-tools is essential for retrieving sequence data from the Sequence Read Archive (SRA), a large repository of publicly available next-generation sequencing data.
• Why it's important: It provides easy access to raw sequencing data (in .sra format), and its tools like prefetch and fasterq-dump are indispensable for converting .sra files into usable FASTQ files.

conda install -c bioconda sra-tools==3.0.8

fastp

• Purpose: fastp is a highly efficient tool for quality control and preprocessing of FASTQ files. It performs functions like adapter trimming, filtering by quality, and basic data analysis.
• Why it's important: Ensuring high-quality sequence data is crucial before downstream analyses such as assembly or mapping. fastp automates the trimming and filtering process, which improves the reliability of the data.

conda install -c bioconda fastp==0.23.4

Step 4: Prepare Workspace

Create a directory to store sequence data and quality check results:

mkdir MAG
cd MAG

Step 5: Download Sequence Data

Using sra-tools to download data directly from the SRA repository:

1. prefetch: Downloads the raw .sra files from the SRA repository.
2. fasterq-dump: Converts .sra files into FASTQ format, which is the standard input format for most sequence processing tools. The --split-files flag ensures that paired-end reads are split into two separate files, and --skip-technical ignores technical reads that do not contribute to biological information.

prefetch SRR23604271 SRR23604268

fasterq-dump SRR23604271 --split-files --skip-technical
fasterq-dump SRR23604268 --split-files --skip-technical

FastQC Installation

What is FastQC and Why it's Important

• Purpose: FastQC is a tool for quality control of raw sequence data. It generates comprehensive reports with metrics like sequence quality scores, GC content, overrepresented sequences, and adapter content.
• Why it's important: Assessing the quality of sequence data is critical before any further analysis. FastQC provides a quick overview to identify any issues such as low-quality reads or contamination, ensuring the reliability of the dataset for downstream processes.

Installation Instructions

FastQC is not available directly via Conda for macOS, so it needs to be downloaded manually:

1. Visit the FastQC download page and download FastQC v0.12.1 (Mac DMG image).
2. Mount the .dmg file and drag the FastQC application to the Applications folder.
3. Unmount the .dmg after installation.

Add FastQC to Your PATH

To run FastQC from the command line in your conda environment or system-wide, you need to add it to your PATH variable.

1. Open Terminal and add FastQC to your PATH by adding this line to your ~/.bash_profile or ~/.zshrc file:

   export PATH=$PATH:/Applications/FastQC.app/Contents/MacOS/

2. Reload your shell configuration:

   source ~/.bash_profile

   Or, if you use Zsh:

   source ~/.zshrc

Verify FastQC Installation

Verify that FastQC has been added to your PATH:

which fastqc

Expected output:

/Applications/anaconda3/envs/Basic_protocol_1/bin/fastqc

Check the version of FastQC:

fastqc --version

Expected output:

FastQC v0.12.1

Fix Permissions (if necessary)

If you encounter issues running FastQC, you may need to make the application executable:

chmod +x /Applications/FastQC.app/Contents/MacOS/fastqc

Now you can run FastQC from any directory by simply typing:

fastqc

Resources

• Conda Documentation
• SRA Toolkit Documentation
• fastp Documentation
• FastQC Download Page

Expected Outputs

• Prefetch output: .sra files downloaded from the SRA.
• Fasterq-dump output: Split FASTQ files (e.g., SRR23604271_1.fastq, SRR23604271_2.fastq).
• Fastp output: Cleaned FASTQ files (e.g., SRR23604271_1_clean.fastq, SRR23604271_2_clean.fastq).
• FastQC output: Quality control reports (.html and .zip files) summarizing sequence quality metrics.

Notes

• Ensure that Conda is correctly installed on your system before proceeding.
• Always make sure your Conda environment is activated (conda activate Basic_protocol_1) when running commands.
• If FastQC is not recognized in your PATH, revisit the steps for adding it to your PATH.

Key Explanations:

• Conda: Manages environments and dependencies to ensure tools don't conflict with each other.
• sra-tools: Essential for fetching publicly available sequence data from SRA.
• fastp: Critical for cleaning sequence data, ensuring the highest quality input for downstream analysis.
• FastQC: Ensures the quality of sequence data, allowing you to spot issues early on.